01631nas a2200181   4500008004100000245004400041210004400085300000600129490000700135520112800142653002901270653002301299653001501322100002201337700002301359700002001382856004701402       2013                        eng d00aComplexities of Horn Description Logics0 aComplexities of Horn Description Logics  a20 v143 aDescription Logics (DLs) have become a prominent paradigm for representing knowledge bases in a variety of application areas. Central to leveraging them for corresponding systems is the provision of a favourable balance between expressivity of the knowledge representation formalism on the one hand, and runtime performance of reasoning algorithms on the other. Due to this, Horn description logics (Horn DLs) have attracted attention since their (worst-case) data complexities are in general lower than their overall (i.e. combined) complexities, which makes them attractive for reasoning with large sets of instance data (ABoxes). However, the natural question whether Horn DLs also provide advantages for schema (TBox) reasoning has hardly been addressed so far. In this paper, we therefore provide a thorough and comprehensive analysis of the combined complexities of Horn DLs. While the combined complexity for many Horn DLs studied herein turns out to be the same as for their non-Horn counterparts, we identify subboolean DLs where Hornness simplifies reasoning. We also provide convenient normal forms for Horn DLs.10acomputational complexity10adescription logics10aHorn logic1 aKrötzsch, Markus1 aRudolph, Sebastian1 aHitzler, Pascal  uhttp://doi.acm.org/10.1145/2422085.242208701617nas a2200229   4500008004100000245008100041210006900122300001100191490000600202520090100208653001401109653002901123653003001152653002901182653002301211100001201234700001501246700001701261700002001278700001701298856007201315       2010                        eng d00aComputational Complexity and Anytime Algorithm for Inconsistency Measurement0 aComputational Complexity and Anytime Algorithm for Inconsistency  a3–210 v43 a<p class="rtejustify">Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first give a complete analysis of the computational complexity of computing inconsistency degrees. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximations of the inconsistency degree from above and below. We show that our algorithm satisfies some desirable properties and give experimental results of our implementation of the algorithm</p>
10aalgorithm10acomputational complexity10ainconsistency measurement10aKnowledge representation10amulti-valued logic1 aMa, Yue1 aQi, Guilin1 aXiao, Guohui1 aHitzler, Pascal1 aLin, Zuoquan  uhttp://www.ijsi.org/ch/reader/view_abstract.aspx?file_no=i41&flag=1